Matthias Haimel

8.9k total citations
10 papers, 199 citations indexed

About

Matthias Haimel is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Genetics. According to data from OpenAlex, Matthias Haimel has authored 10 papers receiving a total of 199 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Pulmonary and Respiratory Medicine and 2 papers in Genetics. Recurrent topics in Matthias Haimel's work include Genomics and Phylogenetic Studies (4 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (2 papers) and Genomics and Rare Diseases (2 papers). Matthias Haimel is often cited by papers focused on Genomics and Phylogenetic Studies (4 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (2 papers) and Genomics and Rare Diseases (2 papers). Matthias Haimel collaborates with scholars based in United Kingdom, Austria and Australia. Matthias Haimel's co-authors include Ewan Birney, D. Staines, Karyn Mégy, Daniel Lawson, F. Valentin, Arnaud Kerhornou, Javier Herrero, Albert J. Vilella, Gautier Koscielny and Andrew Yates and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and Briefings in Bioinformatics.

In The Last Decade

Matthias Haimel

10 papers receiving 198 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Matthias Haimel United Kingdom	6	138	46	44	28	25	10	199
Tao Cheng China	8	125 0.9×	15 0.3×	10 0.2×	17 0.6×	24 1.0×	26	189
Christopher J. Conley United States	7	108 0.8×	97 2.1×	14 0.3×	10 0.4×	20 0.8×	10	222
Lumeng Jia China	6	216 1.6×	49 1.1×	27 0.6×	20 0.7×	33 1.3×	8	251
Melodi Tastemel United States	7	272 2.0×	35 0.8×	27 0.6×	5 0.2×	24 1.0×	8	301
Nicolas Greliche France	6	73 0.5×	75 1.6×	128 2.9×	12 0.4×	12 0.5×	6	242
Rosa Pennisi Italy	6	164 1.2×	17 0.4×	11 0.3×	18 0.6×	17 0.7×	12	197
Samuel M. Gerner Austria	4	87 0.6×	45 1.0×	12 0.3×	8 0.3×	10 0.4×	5	147
Justin T. Brown United States	8	293 2.1×	32 0.7×	10 0.2×	8 0.3×	5 0.2×	12	345
Charles Romfo United States	11	660 4.8×	36 0.8×	17 0.4×	22 0.8×	32 1.3×	14	681
Sophie Rozenzhak United States	6	251 1.8×	37 0.8×	34 0.8×	4 0.1×	63 2.5×	7	296

Countries citing papers authored by Matthias Haimel

Since Specialization

Citations

This map shows the geographic impact of Matthias Haimel's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Matthias Haimel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthias Haimel more than expected).

Fields of papers citing papers by Matthias Haimel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthias Haimel. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Matthias Haimel. The network helps show where Matthias Haimel may publish in the future.

Co-authorship network of co-authors of Matthias Haimel

This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Haimel. A scholar is included among the top collaborators of Matthias Haimel based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthias Haimel. Matthias Haimel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

Kager, Leo, Raúl Jiménez Heredia, Sebastian K. Eder, et al.. (2024). A single‐center cohort study of patients with hereditary spherocytosis in Central Europe reveals a high frequency of novel disease‐causing genotypes. HemaSphere. 8(1). e31–e31. 1 indexed citations

Daniš, Daniel, Julius O.B. Jacobsen, Parithi Balachandran, et al.. (2022). SvAnna: efficient and accurate pathogenicity prediction of coding and regulatory structural variants in long-read genome sequencing. Genome Medicine. 14(1). 44–44. 16 indexed citations

Tolios, Alexander, Stefanie Hofer, Cihan Ay, et al.. (2021). Elevated levels of tissue factor pathway inhibitor in patients with mild to moderate bleeding tendency. Blood Advances. 5(2). 391–398. 20 indexed citations

Tolios, Alexander, Stefanie Hofer, Cihan Ay, et al.. (2021). Thrombomodulin in patients with mild to moderate bleeding tendency. Haemophilia. 27(6). 1028–1036. 9 indexed citations

Shih, Jhih‐Yuan, Matthias Haimel, Marta Bleda, et al.. (2020). SOX17 Deficiency Impairs Tube Network Formation Through the Reduction of Arterial Identity in Pulmonary Arterial Hypertension. A2366–A2366. 1 indexed citations

Haimel, Matthias, et al.. (2018). S42 Characterizing ATP13A3 loss of function in pulmonary arterial hypertension (PAH). A26.2–A27. 3 indexed citations

Ferreiros, Javier, Matthias Haimel, Joaquín Tárraga, et al.. (2017). HGVA: the Human Genome Variation Archive. Nucleic Acids Research. 45(W1). W189–W194. 6 indexed citations

Watson‐Haigh, Nathan S., Catherine A. Shang, Matthias Haimel, et al.. (2013). Next-generation sequencing: a challenge to meet the increasing demand for training workshops in Australia. Briefings in Bioinformatics. 14(5). 563–574. 14 indexed citations

Haimel, Matthias, et al.. (2009). ProteinArchitect: Protein Evolution above the Sequence Level. PLoS ONE. 4(7). e6176–e6176. 1 indexed citations

10.

Kersey, Paul, Daniel Lawson, Ewan Birney, et al.. (2009). Ensembl Genomes: Extending Ensembl across the taxonomic space. Nucleic Acids Research. 38(suppl_1). D563–D569. 128 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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